🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzhei...
Concept Bottleneck Models, ICML 2020
PyTorch Explain: Interpretable Deep Learning in Python.
Fast approximate Shapley values in R
All about explainable AI, algorithmic fairness and more
Implementation of Layerwise Relevance Propagation for heatmapping "deep"...
Explainable Machine Learning in Survival Analysis
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learn...
Model Agnostic Counterfactual Explanations
ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image ...
Implementation of the paper "Shapley Explanation Networks"
A Julia package for interpretable machine learning with stochastic Shapl...
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Reference tables to introduce and organize evaluation methods and measur...
An R package for computing asymmetric Shapley values to assess causality...